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Job Title : Data Quality Engineer (Python + SQL) Location : India (Remote/Hybrid as per project needs) Experience : 4 to 6 Years Shift : US Shift Role Overview : We are seeking a detail-oriented Data Quality Engineer to ensure the reliability, accuracy, and integrity of enterprise data systems. In this role, you will design and implement automated data quality frameworks, validate large datasets, and proactively monitor data pipelines to detect inconsistencies and anomalies. The ideal candidate will have strong expertise in Python, SQL, and modern data quality tools such as Great Expectations, Deequ, or Soda, along with a solid understanding of data validation, profiling, and monitoring in data pipelines. Key Responsibilities : Data Quality & Validation : - Design and implement automated data quality checks across data pipelines - Build validation frameworks using tools like Great Expectations, Deequ, or Soda - Monitor data pipelines and proactively identify data anomalies or inconsistencies - Define and enforce data quality rules, metrics, and thresholds Data Engineering Support : - Write efficient SQL queries to validate and profile large datasets - Develop Python scripts and utilities for automated data validation and monitoring - Work closely with data engineering teams to ensure data reliability across systems - Analyze root causes of data issues and recommend corrective actions Data Governance & Monitoring : - Implement data quality dashboards and monitoring frameworks - Maintain documentation for data validation rules and processes - Support data governance initiatives by enforcing data standards and quality checks - Continuously improve data quality processes and automation Required Skills & Experience : - 4 to 6 years of experience in data quality, data validation, or data engineering roles - Strong proficiency in Python for data validation and automation - Advanced SQL query writing and data analysis skills Hands on experience with data quality tools such as : Great Expectations : - Soda (Soda SQL/Soda Core) - Strong understanding of data profiling, validation, and monitoring techniques - Experience working with large datasets and data pipelines - Strong analytical and troubleshooting skills Good to Have : - Experience working with modern data platforms (Snowflake, Databricks, BigQuery, etc.) - Exposure to workflow orchestration tools such as Airflow - Knowledge of data governance and data lineage concepts - Experience building data quality dashboards and alerts Qualifications : - Bachelors degree in Computer Science, Data Engineering, Information Systems, or related field - Strong communication and collaboration skills - Ability to work effectively in US shift environments .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.